/*
 *   This program is free software: you can redistribute it and/or modify
 *   it under the terms of the GNU General Public License as published by
 *   the Free Software Foundation, either version 3 of the License, or
 *   (at your option) any later version.
 *
 *   This program is distributed in the hope that it will be useful,
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *   GNU General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

/*
 *    EntropyBasedSplitCrit.java
 *    Copyright (C) 1999-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.classifiers.trees.j48;

import weka.core.ContingencyTables;

/**
 * "Abstract" class for computing splitting criteria based on the entropy of a
 * class distribution.
 *
 * @author Eibe Frank (eibe@cs.waikato.ac.nz)
 * @version $Revision$
 */
public abstract class EntropyBasedSplitCrit extends SplitCriterion {

    /** for serialization */
    private static final long serialVersionUID = -2618691439791653056L;

    /**
     * Help method for computing entropy.
     */
    public final double lnFunc(double num) {

        // Constant hard coded for efficiency reasons
        if (num < 1e-6)
            return 0;
        else
            return ContingencyTables.lnFunc(num);
    }

    /**
     * Computes entropy of distribution before splitting.
     */
    public final double oldEnt(Distribution bags) {

        double returnValue = 0;
        int j;

        for (j = 0; j < bags.numClasses(); j++)
            returnValue = returnValue + lnFunc(bags.perClass(j));
        return (lnFunc(bags.total()) - returnValue) / ContingencyTables.log2;
    }

    /**
     * Computes entropy of distribution after splitting.
     */
    public final double newEnt(Distribution bags) {

        double returnValue = 0;
        int i, j;

        for (i = 0; i < bags.numBags(); i++) {
            for (j = 0; j < bags.numClasses(); j++)
                returnValue = returnValue + lnFunc(bags.perClassPerBag(i, j));
            returnValue = returnValue - lnFunc(bags.perBag(i));
        }
        return -(returnValue / ContingencyTables.log2);
    }

    /**
     * Computes entropy after splitting without considering the class values.
     */
    public final double splitEnt(Distribution bags) {

        double returnValue = 0;
        int i;

        for (i = 0; i < bags.numBags(); i++)
            returnValue = returnValue + lnFunc(bags.perBag(i));
        return (lnFunc(bags.total()) - returnValue) / ContingencyTables.log2;
    }
}
